Laundry washing machine color composition analysis during loading

ABSTRACT

A laundry washing machine and method automate the selection of various operational settings for a wash cycle based in part on color composition data collected from a load of articles using a color detection sensor. In some instances, the capture of color composition data is triggered by detected weight changes sensed by a weight sensor as the load of articles is added to a wash tub, and is based in part on the detection of a stable weight in the wash tub for at least a predetermined duration. In addition, in some instances, color compensation data may be used to characterize a load of articles based in part on a color decision algorithm that assigns pixels in the color compensation data to different color categories.

BACKGROUND

Laundry washing machines are used in many single-family and multi-familyresidential applications to clean clothes and other fabric items. Due tothe wide variety of items that may need to be cleaned by a laundrywashing machine, many laundry washing machines provide a wide variety ofuser-configurable settings to control various aspects of a wash cyclesuch as water temperatures and/or amounts, agitation, soaking, rinsing,spinning, etc. The settings cycle can have an appreciable effect onwashing performance, as well as on energy and/or water consumption, soit is generally desirable for the settings used by a laundry washingmachine to appropriately match the needs of each load washed by themachine.

Some laundry washing machines also support user selection of load types,typically based on the types of fabrics and/or items in the load. Somelaundry washing machines, for example, have load type settings such ascolors, whites, delicates, cottons, permanent press, towels, bedding,heavily soiled items, etc. These manually-selectable load typesgenerally represent specific combinations of operational settings thatare optimized for particular load types so that a user is not requiredto select individual values for each of the controllable operationalsettings of a laundry washing machine.

While manual load type selection in many cases simplifies a user'sinteraction with a laundry washing machine, such manual selection stillcan lead to suboptimal performance due to, for example, userinattentiveness or lack of understanding. Therefore, a significant needcontinues to exist in the art for manners of optimizing the performanceof a laundry washing machine for different types of loads, as well asreducing the burden on users when interacting with a laundry washingmachine.

Further, while various control methodologies may be developed tooptimize laundry washing machine performance, a significant challengeassociated with such methodologies is the varied environments withinwhich laundry washing machines may be installed, as a controlmethodology and/or the operational settings used thereby that areoptimized for particular environmental conditions may not be optimal forinstallations that depart significantly from those environmentalconditions. Therefore, a significant need also exists in the art for amanner of adapting the control methodologies and/or operational settingsthat may be used to optimize laundry washing machine performance for usein different installations.

SUMMARY

The invention addresses these and other problems associated with the artby providing a laundry washing machine and method that automate theselection of various operational settings for a wash cycle based in parton color composition data collected from a load of articles using acolor detection sensor. In some instances, the capture of colorcomposition data is triggered by detected weight changes sensed by aweight sensor as the load of articles is added to a wash tub, and isbased in part on the detection of a stable weight in the wash tub for atleast a predetermined duration. In addition, in some instances, colorcompensation data may be used to characterize a load of articles basedin part on a color decision algorithm that assigns pixels in the colorcompensation data to different color categories.

Therefore, consistent with one aspect of the invention, a laundrywashing machine may include a wash tub disposed within a housing, acolor detection sensor positioned to capture color composition data of aload of articles as the load of articles is added to the wash tub, aweight sensor operatively coupled to the wash tub to sense a weight ofthe load of articles as the load of articles is added to the wash tub,and a controller coupled to the color detection sensor and the weightsensor and configured to initiate a plurality of color composition datacaptures with the color detection sensor responsive to detected weightchanges sensed by the weight sensor as the load of articles is added tothe wash tub, the controller configured to initiate each colorcomposition data capture in response at least in part to the weightsensor detecting a stable weight in the wash tub for at least apredetermined duration, where the controller is further configured toset one or more operational settings for a wash cycle based upon theplurality of color composition data captures.

In some embodiments, the controller is configured to detect the stableweight for at least the predetermined duration by determining that aweight change sensed by the weight sensor during the predeterminedduration is less than a stability weight constant. Also, in someembodiments, the controller is configured to detect the stable weightfor at least the predetermined duration by starting a stability timerwhen a weight change subsequent to a prior composition data capture isgreater than an article addition weight constant. Further, in someembodiments, the controller is configured to store a stability weight inconnection with starting the stability timer and reset the stabilitytimer if and the stability weight if the weight change sensed by theweight sensor during the predetermined duration exceeds the stabilityweight constant. In some embodiments, the controller is configured toinitiate a color composition data capture in response to the stabilitytimer reaching the predetermined duration.

In addition, in some embodiments, the controller is further configuredto detect removal of an article from the wash tub using the weightsensor and delete a color composition data capture in response todetecting removal of the article. In some embodiments, the controller isfurther configured to initiate each color composition data capture inresponse at least in part to detection of image stability in the washtub.

In addition, in some embodiments, the controller is configured toinitiate the plurality of color composition data captures in response todetecting an open door, and to determine that all articles in the loadhave been added to the wash tub in response to detecting a closed door.Moreover, in some embodiments, the controller is configured to initiatean additional capture of color composition data after detecting theclosed door, and to delete the additional capture of color compositiondata if a weight change sensed by the weight sensor is less than apredetermined constant. In some embodiments, the controller is furtherconfigured to initiate a capture of an additional color composition datacapture after detecting the closed door in response to detecting thatthe door has been reopened and that the weight sensor has detectedanother article added to the wash tub. Moreover, in some embodiments,the controller is configured to start a sleep timer in response todetecting the open door, to reset the sleep timer in connection witheach color composition data capture, to put the laundry washing machinein a sleep state in response to expiration of the sleep timer, and toawaken the laundry washing machine and initiate a color composition datacapture in response to detection of a weight change by the weight sensorwhile the laundry washing machine is in the sleep state.

In some embodiments, the color detection sensor includes an image sensorconfigured to capture a digital image, and the laundry washing machinefurther includes a light positioned to illuminate the wash tub duringimage capture with the image sensor. In addition, in some embodiments,the controller is further configured to initiate a color decisionalgorithm to characterize the captured color composition data byassigning each of a plurality of pixels in the captured colorcomposition data to one of a plurality of color categories, and tocharacterize the load of articles based upon the characterized colorcompensation data, and to set one or more operational settings for awash cycle based upon the characterization of the load of articles bythe color decision algorithm.

Consistent with another aspect of the invention, a laundry washingmachine may include a wash tub disposed within a housing, a colordetection sensor positioned to capture color composition data of a loadof articles as the load of articles is added to the wash tub, and acontroller coupled to the color detection sensor and configured toinitiate the capture of the color composition data with the colordetection sensor as the load of articles is added to the wash tub, thecontroller further configured to initiate a color decision algorithm tocharacterize the captured color composition data by assigning each of aplurality of pixels in the captured color composition data to one of aplurality of color categories, and to characterize the load of articlesbased upon the characterized color compensation data, where thecontroller is further configured to set one or more operational settingsfor a wash cycle based upon the characterization of the load of articlesby the color decision algorithm.

In some embodiments, the controller is configured to initiate the colordecision algorithm by executing at least a portion of the color decisionalgorithm. Moreover, in some embodiments, the controller is configuredto initiate the color decision algorithm by communicating data from theplurality of color composition data captures to a remote device thatexecutes at portion of the color decision algorithm, and the controlleris further configured to receive result data associated with the colordecision algorithm from the remote device. Also, in some embodiments,the color decision algorithm is configured to assign each of theplurality of pixels in the captured color composition data to one of theplurality of color categories by comparing color data for each pixelagainst a plurality of thresholds associated with the plurality of colorcategories. In some embodiments, the color decision algorithm isconfigured to determine a number of pixels in the captured colorcomposition data that are assigned to each of the plurality of colorcategories, and to characterize the load of articles based upon thedetermined numbers of pixels.

In addition, in some embodiments, the color decision algorithm isconfigured to characterize the load of articles based upon thedetermined numbers of pixels by comparing the determined numbers ofpixels against thresholds associated with one or more of the pluralityof color categories. Also, in some embodiments, the plurality of colorcategories to which the pixels are assigned includes a whites colorcategory, a lights color category, and a darks color category, and thecolor decision algorithm is configured to characterize the load ofarticles based upon the determined numbers of pixels by characterizingthe load of articles as a whites load in response to a majority of thedetermined numbers of pixels being assigned to the whites color categoryand the determined number of pixels assigned to the whites colorcategory meeting a whites threshold, characterizing the load of articlesas a lights load in response to a majority of the determined numbers ofpixels being assigned to the lights color category and the determinednumber of pixels assigned to the lights color category meeting a lightsthreshold, and characterizing the load of articles as a darks load inresponse to a majority of the determined numbers of pixels beingassigned to the darks color category and the determined number of pixelsassigned to the darks color category meeting a darks threshold.

Moreover, in some embodiments, the plurality of color categories furtherincludes a reds color category, and the color decision algorithm isfurther configured to characterize the load of articles as a reds loadin response to the determined number of pixels assigned to the redscolor category meeting a reds threshold.

Consistent with another aspect of the invention, a method of operating alaundry washing machine may include capturing color composition data ofa load of articles as the load of articles is added to a wash tub usinga color detection sensor, sensing a weight of the load of articles asthe load of articles is added to the wash tub using a weight sensoroperatively coupled to the wash tub, initiating a plurality of colorcomposition data captures with the color detection sensor responsive todetected weight changes sensed by the weight sensor as the load ofarticles is added to the wash tub, where each color composition datacapture is initiated in response to the weight sensor detecting a stableweight in the wash tub for at least a predetermined duration, initiatinga color decision algorithm to characterize the captured colorcomposition data by assigning each of a plurality of pixels in thecaptured color composition data to one of a plurality of colorcategories, and to characterize the load of articles based upon thecharacterized color compensation data, and setting one or moreoperational settings for a wash cycle based upon the plurality of colorcomposition data captures.

Other embodiments may include various methods of operating a laundrywashing machine utilizing the various operations described above.

These and other advantages and features, which characterize theinvention, are set forth in the claims annexed hereto and forming afurther part hereof. However, for a better understanding of theinvention, and of the advantages and objectives attained through itsuse, reference should be made to the Drawings, and to the accompanyingdescriptive matter, in which there is described example embodiments ofthe invention. This summary is merely provided to introduce a selectionof concepts that are further described below in the detaileddescription, and is not intended to identify key or essential featuresof the claimed subject matter, nor is it intended to be used as an aidin limiting the scope of the claimed subject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a perspective view of a top-load laundry washing machineconsistent with some embodiments of the invention.

FIG. 2 is a perspective view of a front-load laundry washing machineconsistent with some embodiments of the invention.

FIG. 3 is a functional vertical section of the laundry washing machineof FIG. 1 .

FIG. 4 is a block diagram of an example control system for the laundrywashing machine of FIG. 1 .

FIG. 5 is a flowchart illustrating an example sequence of operations forimplementing a wash cycle in the laundry washing machine of FIG. 1 .

FIG. 6 is a graph illustrating plots of fluid levels over time forexample polyester, towels and mixed loads.

FIG. 7 is a flowchart illustrating another example sequence ofoperations for implementing a wash cycle in the laundry washing machineof FIG. 1 .

FIG. 8 is a flowchart illustrating an example sequence of operations forperforming the load type determination referenced in FIG. 7 .

FIGS. 9A-9C illustrate a flowchart for an example sequence of operationsfor capturing and analyzing images of a load in the laundry washingmachine of FIG. 1 .

FIGS. 10A-10B illustrate a flowchart for an example sequence ofoperations for performing the image analysis referenced in FIG. 9C.

FIGS. 11A-11C illustrate a flowchart for an example sequence ofoperations for calibrating the laundry washing machine of FIG. 1 .

DETAILED DESCRIPTION

Embodiments consistent with the invention may be used in connection withautomating the operation of a laundry washing machine. In particular, insome embodiments consistent with the invention, a laundry washingmachine may include one or both of an absorption-based load typeselection process and a color-based load type selection process that maybe used separately or together to select a load type for a load disposedin a wash tub, and from the selected load type, determine one or moreoperational settings for a wash cycle performed by the laundry washingmachine. In connection with such selection processes, article alertsand/or load type modifications may be generated in some embodiments inresponse to the detection of outlier articles in a load. Further, insome instances, various aspects of the selection processes may becalibrated for a particular installation of a laundry washing machine,e.g., based upon ambient lighting conditions, water supply pressure, andthe weight of the wash tub itself.

In this regard, a load type may be considered to represent one of aplurality of different characteristics, categories, classes, subclasses,etc. that may be used to distinguish different loads from one another,and for which it may be desirable to define particular operationalsettings or combinations of operational settings for use in washingloads of that particular load type. In one embodiment discussed andillustrated hereinafter, load types may be distinguished based upondifferent fabric types or absorption characteristics (e.g., natural,cotton, wool, silk, synthetic, polyester, permanent press, wrinkleresistant, blends, etc.) and/or based upon color composition, e.g.,(colors, darks, reds, whites, lights, mixed, etc.), and it will beappreciated that fabric types and color composition may be used togetheror separately in different embodiments (i.e., some embodiments may useonly fabric types and some embodiments may use only color composition).Load types may also be based in some embodiments at least in part ondifferent article types (e.g., garments, towels, bedding, delicates,etc.). In addition, separate load types may be used to represent fabrictype and color composition in some embodiments, e.g., characterizing aload as a load of cotton whites or polyester darks, etc.

It will be appreciated, however, that load types may be defined basedupon additional or alternative categorizations, e.g., durability(delicates, work clothes, etc.) and soil level (lightly soiled, normallysoiled, heavily soiled loads, etc.), among others. Load types may alsorepresent categories of loads that are unnamed, and that simplyrepresent a combination of characteristics for which certaincombinations of operational settings may apply, particularly as it willbe appreciated that some loads may be unsorted and may include acombination of different items that themselves have differentcharacteristics. Therefore, in some embodiments, a load type may beassociated with a combination of operational settings that will beapplied to a range of different loads that more closely match that loadtype over other possible load types.

An operational setting, in this regard, may include any number ofdifferent configurable aspects of a wash cycle performed by a laundrywashing machine including, but not limited to, a wash water temperature,a rinse water temperature, a wash water amount, a rinse water amount, aspeed or stroke of agitation during washing and/or rinsing, a spinspeed, whether or not agitation is used during washing and/or rinsing, aduration of a wash, rinse, soak, or spin phase of a wash cycle, a numberof repeats of a wash, rinse, soak or spin phase, selection betweendifferent rinse operation types such as a spray rinse operation or adeep fill rinse operation, pre-treatment such as soaking over time witha prescribed water temperature and specific agitation stroke, etc.

As will become more apparent below, in some embodiments of theinvention, a load type may be dynamically selected during or prior to aninitial fill phase of a wash cycle, i.e., the phase of a wash cycle inwhich water is first introduced into a wash tub, and generally prior toany agitation of the load and/or draining of fluid from the wash tub,and generally without any extended soaking of the load. Thus, incontrast to some conventional approaches, load type selection may beperformed in many embodiments with little or no delay in the initialfill phase, and thus, with little or no impact on the duration of theoverall wash cycle. It will be appreciated, however, that in someembodiments, a load may be agitated or at least rotated during a portionof the initial fill phase, e.g., to facilitate a determination of theweight of the load.

Numerous variations and modifications will be apparent to one ofordinary skill in the art, as will become apparent from the descriptionbelow. Therefore, the invention is not limited to the specificimplementations discussed herein.

Turning now to the drawings, wherein like numbers denote like partsthroughout the several views, FIG. 1 illustrates an example laundrywashing machine 10 in which the various technologies and techniquesdescribed herein may be implemented. Laundry washing machine 10 is atop-load washing machine, and as such includes a top-mounted door 12 ina cabinet or housing 14 that provides access to a vertically-orientedwash tub 16 housed within the cabinet or housing 14. Door 12 isgenerally hinged along a side or rear edge and is pivotable between theclosed position illustrated in FIG. 1 and an opened position (notshown). When door 12 is in the opened position, clothes and otherwashable items may be inserted into and removed from wash tub 16 throughan opening in the top of cabinet or housing 14. Control over washingmachine 10 by a user is generally managed through a control panel 18disposed on a backsplash and implementing a user interface for thewashing machine, and it will be appreciated that in different washingmachine designs, control panel 18 may include various types of inputand/or output devices, including various knobs, buttons, lights,switches, textual and/or graphical displays, touch screens, etc. throughwhich a user may configure one or more settings and start and stop awash cycle.

The embodiments discussed hereinafter will focus on the implementationof the hereinafter-described techniques within a top-load residentiallaundry washing machine such as laundry washing machine 10, such as thetype that may be used in single-family or multi-family dwellings, or inother similar applications. However, it will be appreciated that theherein-described techniques may also be used in connection with othertypes of laundry washing machines in some embodiments. For example, theherein-described techniques may be used in commercial applications insome embodiments. Moreover, the herein-described techniques may be usedin connection with other laundry washing machine configurations. FIG. 2, for example, illustrates a front-load laundry washing machine 20 thatincludes a front-mounted door 22 in a cabinet or housing 24 thatprovides access to a horizontally-oriented wash tub 26 housed within thecabinet or housing 24, and that has a control panel 28 positionedtowards the front of the machine rather than the rear of the machine asis typically the case with a top-load laundry washing machine.Implementation of the herein-described techniques within a front-loadlaundry washing machine would be well within the abilities of one ofordinary skill in the art having the benefit of the instant disclosure,so the invention is not limited to the top-load implementation discussedfurther herein.

FIG. 3 functionally illustrates a number of components in laundrywashing machine 10 as is typical of many washing machine designs. Forexample, wash tub 16 may be vertically oriented, generally cylindricalin shape, opened to the top and capable of retaining water and/or washliquor dispensed into the washing machine. Wash tub 16 may be supportedby a suspension system such as a set of support rods 30 withcorresponding vibration dampening springs 32.

Disposed within wash tub 16 is a wash basket 34 that is rotatable abouta generally vertical axis A by a drive system 36. Wash basket 34 isgenerally perforated or otherwise provides fluid communication betweenan interior 38 of the wash basket 34 and a space 40 between wash basket34 and wash tub 16. Drive system 36 may include, for example, anelectric motor and a transmission and/or clutch for selectively rotatingthe wash basket 34. In some embodiments, drive system 36 may be a directdrive system, whereas in other embodiments, a belt or chain drive systemmay be used.

In addition, in some embodiments an agitator 42 such as an impeller,auger or other agitation element may be disposed in the interior 38 ofwash basket 34 to agitate items within wash basket 34 during a washingoperation. Agitator 42 may be driven by drive system 36, e.g., forrotation about the same axis as wash basket 34, and a transmissionand/or clutch within drive system 36 may be used to selectively rotateagitator 42. In other embodiments, separate drive systems may be used torotate wash basket 34 and agitator 42.

A water inlet 44 may be provided to dispense water into wash tub 16. Insome embodiments, for example, hot and cold valves 46, 48 may be coupledto external hot and cold water supplies through hot and cold inlets 50,52, and may output to one or more nozzles 54 to dispense water ofvarying temperatures into wash tub 16. In addition, a pump system 56,e.g., including a pump and an electric motor, may be coupled between alow point, bottom or sump in wash tub 16 and an outlet 58 to dischargegreywater from wash tub 16. In some embodiments, it may be desirable toutilize multiple nozzles 54, and in some instances, oscillating nozzles54, such that water dispensed into the wash tub is evenly distributedover the top surface of the load. As will become more apparent below, insome instances, doing so may maximize the amount of water absorbed bythe load prior to water reaching the bottom of the wash tub and beingsensed by a fluid level sensor.

In some embodiments, laundry washing machine 10 may also include adispensing system 60 configured to dispense detergent, fabric softenerand/or other wash-related products into wash tub 16. Dispensing system60 may be configured in some embodiments to dispense controlled amountsof wash-related products, e.g., as may be stored in a reservoir (notshown) in laundry washing machine 10. In other embodiments, dispensingsystem 60 may be used to time the dispensing of wash-related productsthat have been manually placed in one or more reservoirs in the machineimmediately prior to initiating a wash cycle. Dispensing system 60 mayalso, in some embodiments, receive and mix water with wash-relatedproducts to form one or more wash liquors that are dispensed into washtub 16. In still other embodiments, no dispensing system may beprovided, and a user may simply add wash-related products directly tothe wash tub prior to initiating a wash cycle.

It will be appreciated that the particular components and configurationillustrated in FIG. 3 is typical of a number of common laundry washingmachine designs. Nonetheless, a wide variety of other components andconfigurations are used in other laundry washing machine designs, and itwill be appreciated that the herein-described functionality generallymay be implemented in connection with these other designs, so theinvention is not limited to the particular components and configurationillustrated in FIG. 3 .

Further, to support various automated functionality described herein,laundry washing machine 10 also may also include one or more of sensors,including, among others, a weight sensor, a fluid level sensor, aturbidity sensor, a flow sensor, and/or a color detection sensor.

A weight sensor may be used to generate a signal that varies based inpart on the mass or weight of the contents of wash tub 16. In theillustrated embodiment, for example, a weight sensor may be implementedin laundry washing machine 10 using a single load cell 62 coupled to oneof the support rods 30, or alternatively on other structures supportingthe wash tub, e.g., a leg, spring or damper. Load cell 62 may be anelectro-mechanical sensor that outputs a signal that varies with adisplacement based on load or weight, and thus outputs a signal thatvaries with the weight of the contents of wash tub 16. Multiple loadcells 62 may be used in some embodiments, while in other embodiments,other types of transducers or sensors that generate a signal that varieswith applied force, e.g., strain gauges, may be used. Furthermore, whilea single load cell 62, which is offset from a rotational axis A of washbasket 34, is illustrated as supporting wash tub 16 on a support rod 30,the load cells, or other appropriate transducers or sensors, may bepositioned elsewhere in a laundry washing machine to generate one ormore signals that vary in response to the weight of the contents of washtub 16. In some embodiments, for example, transducers may be used tosupport an entire load washing machine, e.g., one or more feet of amachine. Other types and/or locations of transducers suitable forgenerating a signal that varies with the weight of the contents of awash tub will be apparent to one of ordinary skill in the art having thebenefit of the instant disclosure. In addition, in some embodiments, aweight sensor may also be used for vibration sensing purposes, e.g., todetect excessive vibrations resulting from an out-of-balance load. Inother embodiments, however, no vibration sensing may be used, while inother embodiments, separate sensors may be used to sense vibrations.Further, in some embodiments, a single load cell or other transducer maybe used (e.g., disposed proximate a corner of the housing), and the washbasket may be rotated when sensing the weight of the load such that aweight may be determined by averaging multiple weight values capturedduring rotation of the wash basket.

A fluid level sensor may be used to generate a signal that varies withthe level or height of fluid in wash tub 16. In the illustratedembodiment, for example, a fluid level sensor may be implemented using apressure sensor 64 in fluid communication with a low point, bottom orsump of wash tub 16 through a tube 66 such that a pressure sensed bypressure sensor 64 varies with the level of fluid within the wash tub.It will be understood that the addition of fluid to the wash tub willgenerate a hydrostatic pressure within the tube that varies with thelevel of fluid in the wash tub, and that may be sensed, for example,with a piezoelectric or other transducer disposed on a diaphragm orother movable element. It will be appreciated that a wide variety ofpressure sensors may be used to provide fluid level sensing, including,among others, combinations of pressure switches that trigger atdifferent pressures. It will also be appreciated that fluid level in thewash tub may also be sensed using various non-pressure based sensors,e.g., optical sensors, laser sensors, etc.

Additional sensors may also be incorporated into laundry washing machine10. For example, in some embodiments, a turbidity sensor 68 may be usedto measure the turbidity or clarity of the fluid in wash tub 16, e.g.,to sense the presence or relative amount of various wash-relatedproducts such as detergents or fabric softeners and/or to sense thepresence or relative amount of soil in the fluid. Further, in someembodiments, turbidity sensor 68 may also measure other characteristicsof the fluid in wash tub 16, e.g., conductivity and/or temperature. Inother embodiments, separate sensors may be used to measure turbidity,conductivity and/or temperature, and further, other sensors may beincorporated to measure additional fluid characteristics. In otherembodiments, no turbidity sensor may be used.

In addition, in some embodiments, a flow sensor 70 such as one or moreflowmeters may be used to sense an amount of water dispensed into washtub 16. In other embodiments, however, no flow sensor may be used.Instead, water inlet 44 may be configured with a static and regulatedflow rate such that the amount of water dispensed is a product of theflow rate and the amount of time the water is dispensed. Therefore, insome embodiments, a timer may be used to determine the amount of waterdispensed into wash tub 16. In addition, as will be discussed in greaterdetail below, in some instances a calibration process may be performedto determine a water supply pressure and thereby determine acorresponding flow rate from which the amount of water dispensed may bedetermined.

Furthermore, in some embodiments, a color detection sensor 72 may beused to sense the colors of items in a load to be washed by laundrywashing machine 10. In some in instances, color detection sensor 72 maybe located proximate an opening of the wash tub 16 and may capture colorcomposition data of one or more items. In such embodiments, colordetection sensor 72 may capture the color composition data as theitem(s) are added to the wash tub 16, and may be positioned in someembodiments with a field of view focused downwardly towards the bottomof the wash tub. In other embodiments, however, color detection sensor72 may be oriented generally upwardly facing to capture colorcomposition data of items prior to the items reaching the bottom of thewash tub. Other positions for color detection sensor 72 may be used inother embodiments, e.g., on a door, proximate a top edge of a door on afront-load laundry washing machine, and in other locations suitable forcapturing data from items prior to, during, or after loading into a washtub.

In some embodiments, color detection sensor 72 may be an image sensor, acamera, a spectrometer, or any other type of sensor or combination ofsensors capable of capturing electromagnetic radiation in variousspectra (including the visible light spectrum light in some embodiments,and in some embodiments, other spectra such as infrared, ultraviolet,etc.), and color composition data may be in any form that represents theelectromagnetic radiation detected by the sensor. In some embodiments,for example, color detection sensor 72 may be a visible light camera orimage sensor, and the color composition data may be in a form of one ormore images or captures including two or three dimensional arrays ofpixels representing color, intensity and/or other light characteristics.A color composition data capture may include a single image in someembodiments, while in other embodiments a color composition data capturemay include a sequence of images or a sequence of frames from a videostream, among other alternatives.

In some embodiments, for example, color composition data may be in theform of one or more color models, including, but not limited to the RGBcolor model, the CMKY color model, or the like, and the colorcomposition data may include arrays of numerical values representingintensities of different color components (for example, in the RGB colormodel the intensities of red, green, and/or blue) captured by colordetection sensor 72. In some embodiments, color detection sensor 72captures may be initiated in response to detection of a weight changeresulting from one or more items being added to wash tub, e.g., assensed by weight sensor 62. In other embodiments, color detection sensor72 may continuously capture color composition data (e.g., in a videoformat) over a period of time, e.g., started and stopped based uponopening and closing of door 12.

In some embodiments, color detection sensor 72 may also be used todetect a stain on the item(s). In some embodiments, stain detection maybe done in conjunction and/or simultaneously with capturing colorcomposition data; while in other embodiments, stain detection and thecapture of color composition data may be separate and discrete functionsof color detection sensor 72. One or more parameters of the wash cyclemay be configured based on the detection of a stain in some embodiments,e.g., to utilize a pretreatment, such as a soak, in order to aid inremoving the stain, and in some embodiments, one or more characteristicsof the detected stain may be determined, e.g., composition of the stain(e.g. oil, food, etc.), size of the stain, intensity or the stain, etc.,with one or more wash cycle parameters adjusted based upon thedetermined characteristics of the stain. In still other embodiments, theuse of a stain removal tool may be recommended (e.g., via a notificationto a user via a user interface of the laundry washing machine or amobile computing device) based on the characteristic(s) of the stain.

In some embodiments, a retractable cover 74 may selectively cover colordetection sensor 72 and may be able to transition between covering andexposing substantially all of color detection sensor 72. In suchembodiments, the retractable cover 74 may be configured to initiateautomatic retraction in response to the open/closed status of door 12,and may be desirable where color detection sensor 72 is disposed withina location in the wash tub where it could be exposed to water,detergent, and the like during a wash cycle. Various retractable coverdesigns may be used, e.g., slidable planar covers, iris-type covers,pivotable covers, etc., while in other embodiments, no retractable covermay be used.

Now turning to FIG. 4 , laundry washing machine 10 may be under thecontrol of a controller 80 that receives inputs from a number ofcomponents and drives a number of components in response thereto.Controller 80 may, for example, include one or more processors 82 and amemory 84 within which may be stored program code for execution by theone or more processors. The memory may be embedded in controller 80, butmay also be considered to include volatile and/or non-volatile memories,cache memories, flash memories, programmable read-only memories,read-only memories, etc., as well as memory storage physically locatedelsewhere from controller 80, e.g., in a mass storage device or on aremote computer interfaced with controller 80.

As shown in FIG. 4 , controller 80 may be interfaced with variouscomponents, including the aforementioned drive system 36, hot/cold inletvalves 46, 48, pump system 56, weight sensor 62, fluid level sensor 64,turbidity sensor 68, flow sensor 70, color detection sensor 72 andretractable cover 74. In addition, controller 80 may be interfaced withadditional components such as a door switch 86 that detects whether door12 is in an open or closed position and a door lock 88 that selectivelylocks door 12 in a closed position. Moreover, controller 80 may becoupled to a user interface 90 including various input/output devicessuch as knobs, dials, sliders, switches, buttons, lights, textual and/orgraphics displays, touch screen displays, speakers, image capturedevices, microphones, etc. for receiving input from and communicatingwith a user. In some embodiments, controller 80 may also be coupled toone or more network interfaces 92, e.g., for interfacing with one ormore external devices 94 via wired and/or wireless networks such asEthernet, Bluetooth, NFC, cellular and other suitable networks.Additional components may also be interfaced with controller 80, as willbe appreciated by those of ordinary skill having the benefit of theinstant disclosure. Moreover, in some embodiments, at least a portion ofcontroller 80 may be implemented externally from a laundry washingmachine, e.g., within a mobile device, a cloud computing environment,etc., such that at least a portion of the functionality described hereinis implemented within the portion of the controller that is externallyimplemented.

In some embodiments, controller 80 may operate under the control of anoperating system and may execute or otherwise rely upon various computersoftware applications, components, programs, objects, modules, datastructures, etc. In addition, controller 80 may also incorporatehardware logic to implement some or all of the functionality disclosedherein. Further, in some embodiments, the sequences of operationsperformed by controller 80 to implement the embodiments disclosed hereinmay be implemented using program code including one or more instructionsthat are resident at various times in various memory and storagedevices, and that, when read and executed by one or more hardware-basedprocessors, perform the operations embodying desired functionality.Moreover, in some embodiments, such program code may be distributed as aprogram product in a variety of forms, and that the invention appliesequally regardless of the particular type of computer readable mediaused to actually carry out the distribution, including, for example,non-transitory computer readable storage media. In addition, it will beappreciated that the various operations described herein may becombined, split, reordered, reversed, varied, omitted, parallelizedand/or supplemented with other techniques known in the art, andtherefore, the invention is not limited to the particular sequences ofoperations described herein.

Now turning to FIG. 5 , and with continuing reference to FIGS. 3-4 , asequence of operations 100 for performing a wash cycle in laundrywashing machine 10 is illustrated. A typical wash cycle includesmultiple phases, including a load phase 102 where a load of articles isloaded into the wash tub, a fill phase 104 where the wash tub isinitially filled with water, a wash phase 106 where the load is washedby agitating the load with a wash liquor formed from the fill water andany wash products added manually or automatically by the washingmachine, a rinse phase 108 where the load is rinsed of detergent and/orother wash products (e.g., using a deep fill rinse where the wash tub isfilled with fresh water and the load is agitated and/or a spray rinsewhere the load is sprayed with fresh water while spinning the load), anda spin phase 110 where the load is spun rapidly while water is drainedfrom the wash tub to reduce the amount of moisture in the load.

It will be appreciated that wash cycles can also vary in a number ofrespects. For example, additional phases, such as a pre-soak phase, maybe included in some wash cycles, and moreover, some phases may berepeated, e.g., including multiple rinse and/or spin phases. Each phasemay also have a number of different operational settings that may bevaried for different types of loads, e.g., different times or durations,different water temperatures, different agitation speeds or strokes,different rinse operation types, different spin speeds, different wateramounts, different wash product amounts, etc.

In some embodiments consistent with the invention, a load type may beautomatically and dynamically selected prior to or during the initialfill phase 104 based at least in part on multiple times determined basedupon various fluid levels sensed by fluid level sensor 64 during andafter the dispensation of water into the wash tub by water inlet 44, andassociated with the absorbency of the articles in the load. In someembodiments, the automatic and dynamic selection may be performed inresponse to user selection of a particular mode (e.g., an “automatic”mode), while in other embodiments, automatic and dynamic selection maybe used for all wash cycles. In still other embodiments, automatic anddynamic selection may further be based upon additional input provided bya user, e.g., soil level, article type, fabric type, article durability,etc.

In some embodiments, dynamic selection may be based at least in part onjudging the absorptivity of the fabric in the load against the weight ofthe load. A dry weight may be determined for the load in someembodiments at the beginning of a washing cycle (e.g., at the beginningof the fill phase) using a weight sensor and prior to dispensing anywater into the wash tub. Thereafter, water may dispensed into the washtub, and fluid levels sensed by a fluid level sensor while dispensingwater into the wash tub as well as after water dispensing has beenpaused or stopped may be used to determine multiple times that may becompared against various load type criteria to select a load type fromamong a plurality of different load types. The load type may then beused, for example, to determine if and how much additional water shouldbe added for the initial fill, as well as other operational settings forthe wash cycle.

As will become more apparent below, in particular, a first time at whichthe fluid level reaches a predetermined fluid level while dispensingwater into the wash tub and a peak time at which the fluid levelstabilizes after the dispensing of water into the wash tub has beenstopped or paused may be used to categorize a load into one of multipleload types, as both times are affected in part by the absorbency of thearticles in a load. In some instances, the first time alone may be ableto categorize some loads, as, for example, the first time may berelatively short for loads containing only low absorbency fabrics suchas polyesters and other synthetic materials, or may be relatively longfor loads containing highly absorbent articles or fabrics such as cottonarticles, bedding or towels. By incorporating the peak time into thedetermination, however, it has been found that additional loads may beappropriately categorized, e.g., loads where absorbency is such that thefirst time alone is unable to suitably categorize the load. In addition,in some embodiments, the first time may be a sense time where water isfirst detected by a fluid level sensor, and an additional time, e.g., afill time at which the fluid level reaches another predetermined fluidlevel such as a desired minimum fill level while dispensing water intothe wash tub, may also be incorporated into the determination tocategorize additional loads.

In addition, as will also become more apparent below, the weight of theload may also factor into the dynamic detection of load type, e.g., bydetermining appropriate criteria against which the times are comparedwhen determining whether a load is appropriately categorized into aparticular load type. Further, as will also become more apparent below,in some instances it may not be necessary to wait until all of the timeshave been determined, as in some cases an earlier time may be used toappropriately categorize a load without waiting for determinations oflater times, thereby accelerating the load type determination.

In some instances, for example, if a load type determination can be madeprior to filling to a predetermined minimum level and allowing the fluidlevel to stabilize, it may not be necessary to stop or pause filling,and instead filling may continue uninterrupted to a dynamicallycalculated fluid level based on the selected load type. Doing so maytherefore shorten the initial fill phase and thus the overall wash cycleduration.

In one embodiment illustrated and discussed hereinafter, for example,four different load types may be defined, a polyester load type thatrepresents a load that is entirely or mostly comprised of polyesterarticles (which tend to be minimally absorbent), a cotton load type thatis entirely or mostly comprised of cotton articles (which tend to befairly absorbent), a towels load type that is entirely or mostlycomprised of towels (which tend to be highly absorbent), and a mixedload type that, based upon a general absorbency, is likely comprised ofsome mixture of polyester and cotton articles). It will be appreciated,however, that the number and configurations of load types may vary indifferent embodiments, so the invention is not limited to the specificcombination of load types described herein.

In addition, in this embodiment, three times may be recorded during theinitial fill phase based upon fluid levels. A first time, referred to asa sense time, is a time during the initial fill phase that a fluid levelchange is first sensed by the fluid level sensor, i.e., a first detectedchange in fluid level sensed by the fluid level sensor. It will beappreciated, in particular, that when water is first dispensed into thewash tub and onto the load, the fluid level sensor will initially notdetect any water at the bottom of the wash tub for some period of time,and generally not until the articles in the load have become mostlysaturated with water. Thus, as the absorbency of the load increases, thesense time will generally increase as well.

A second time, referred to as a fill time, is a time during the initialfill phase that the fluid level reaches a predetermined fluid level,e.g., a minimum fluid level for the initial fill, representing theminimum amount of water that would be recommended for the loadregardless of type. In some embodiments, however, a fluid leveldifferent from a minimum fluid level may be used, and further while insome embodiments the predetermined fluid level may be a constant fluidlevel, in other embodiments the predetermined fluid level may be variedbased upon weight and/or other load characteristics (e.g., based uponuser input, such as soil level, load size, etc.). As with the sensetime, the fill time also generally increases with the absorbency of theload.

A third time, referred to as a peak time, is a time during the initialfill phase that the fluid level stabilizes after water dispensing hasbeen stopped or paused. In particular, it will be appreciated that afterthe water inlet is shut off, the fluid level in the wash tub willgenerally continue to increase as water drips from the load. The peaktime may be measured based upon when the fluid level stabilizes, i.e.,when the fluid level stops increasing. In some embodiments, thisstabilization may be based upon sensing no change in the fluid level (oralternatively, a change below a predetermined threshold) for apredetermined stabilization duration, e.g., about 15 seconds. As withthe sense and fill times, the peak time also generally increases withthe absorbency of the load. Furthermore, the peak time may be adjustedin some embodiments to not include the stabilization duration, i.e.,such that the peak time is representative of the time at which the fluidlevel ceased increasing.

It will be appreciated that in other embodiments, additional times maybe used, and in some embodiments, only one of the first and second timesmay be used. Furthermore, where the load type may be determined from thefirst time alone, neither of the second or third times may need to bedetermined, and where the load type may be determined from the first andsecond times, the third time may not need to be determined.

In addition, it will be appreciated that the multiple times that aredetermined in connection with selecting a load type are generally timesrelative to one or more points of reference, and thus are associatedwith various durations from various points of reference. In theillustrated embodiment, for example, each of the first and second timesmay be used to calculate durations from the beginning of waterdispensing, while the third time may be used to calculate a durationfrom the point at which water dispensing is stopped or paused. In someinstances, for example, the duration may be determined based upon thedifference between the second and third times, given that in theillustrated embodiment water dispensing is stopped at the second time.The invention, however, is not limited to durations that are relative tothese particular points of reference, so it will be appreciated that inother embodiments each of the times used in dynamic load type selectionmay be used to determine durations relative to other points ofreference, and that each of the times may share a common point ofreference or may be based on a completely separate point of reference indifferent embodiments.

Blocks 112-128 of FIG. 5 , for example, illustrate an example sequenceof operations capable of being performed during initial fill phase 104in order to dynamically select a load type consistent with someembodiments of the invention. As illustrated by block 112, for example,a dry load weight may be determined using a weight sensor, and then thewater inlet may be controlled to start dispensing water in block 114.Thereafter, when a change in the fluid level is first sensed by thefluid level sensor, the time at which this occurs may be recorded as thesense time in block 116. Furthermore, when a predetermined fluid level(e.g., a minimum fill level) is sensed by the fluid level sensor, thetime at which this occurs may be recorded as the fill time in block 118.

In addition, when the predetermined fluid level is reached, the waterinlet is controlled to stop dispensing water in block 120, and when thefluid level is determined to be stabilized (e.g., when the fluid levelremains substantially constant for at least 15 seconds), the time atwhich this occurs (or alternatively the beginning time at which thefluid level stopped increasing) may be recorded as the peak time inblock 122.

Next, in block 124, the load type is determined based upon the first,second and third times and the dry load weight (in a manner discussed infurther detail below), and in block 126, the wash cycle is configured,e.g., based at least in part upon the determined load type. For example,each load type may be associated with a set of operational settingsstored in controller 80 such that selection of a particular load typecauses controller 80 to access the set of operational settings for theselected load type when completing the remainder of the wash cycle. Inaddition, as will become more apparent below, in some embodiments colorcomposition data, collected by a color detection sensor, may also beused in lieu of or in combination with the first, second and third timesand the dry load weight to determine the load type in block 124 and/orotherwise configure the wash cycle in block 126.

Next, block 128 optionally dispenses an additional amount of water tocomplete the fill phase. For example, the additional amount of water maybe selected to provide a total amount of dispensed water selected basedupon load type or selected via a separate load size selection by theuser. In other embodiments, the amount of water dispensed in blocks114-120 may be the total amount of water dispensed during the fillphase, and block 128 may be omitted. Nonetheless, in some embodiments,even when no additional water is dispensed after selecting load type,the load type may be selected prior to transitioning to the wash phase,and in some instances prior to any agitation of the load and/or drainingof fluid from the wash tub. Furthermore, it will be appreciated that theamount of time expended selecting the load type may be minimal or evenimperceptible in some embodiments.

As noted above, in some embodiments, color composition analysis may alsobe performed on the articles in a load in order to determine the loadtype in block 124 or configure one or more operational settings for awash cycle in block 126. Blocks 130-138, for example, illustrate oneexample sequence of operations capable of being performed during a loadphase 102 of the wash cycle in order to collect and analyze colorcomposition data associated with a load. In the illustrated embodiment,this data collection may be performed during a load phase of the washcycle, which generally refers to the portion of a wash cycle duringwhich articles are loaded into the machine. It will be appreciated thatthis load phase may not be considered to be part of the wash cycleitself in some embodiments, since in some embodiments the user will loadthe articles prior to invoking any explicit command to start a washcycle or even explicitly power on the laundry washing machine. In someinstances, for example, a door switch may be used to automaticallyactivate and/or deactivate color composition collection in someembodiments, even where the user has not explicitly selected a usercontrol to power on or start a wash cycle. Generally, however, colorcomposition data collection will be performed in the illustratedembodiments at some point during an initial loading of articles into thelaundry washing machine, and generally prior to filling the wash tubwith water.

In the embodiment illustrated in FIG. 5 , for example, load phase 102begins in block 130 when opening of door 12 is detected (e.g., via doorswitch 86 of FIG. 4 ), and in block 132, the load cell 62 is tared togenerate a baseline load cell reading for the empty wash tub. Next, inblock 134, weight changes detected by the load cell are monitored andused to trigger the capture of images by color detection sensor 72(e.g., a camera), thereby collecting images as articles are loaded intothe wash tub. Then, in block 136, closing of door 12 is detected,thereby signifying that the load has been loaded into the laundrywashing machine. Block 138 then performs color composition analysis onthe collected images, e.g., to categorize the load into one of aplurality of color categories, e.g., whites, lights, darks, reds, mixedor some other collection of visually-distinguishable categories. Theresult of the color composition analysis may then be used in thedetermination of load type in block 124 and/or in the configuration ofthe wash cycle in block 126.

As noted above, absorption characteristics and color characteristics ofa load may be used together to configure a wash cycle in someembodiments, while in other embodiments, only one of absorptioncharacteristics and color characteristics may be used. Further detailsregarding the determination of each of the different types ofcharacteristics are provided in greater detail below.

Load Type Selection Based on Absorption Characteristics During InitialFill

As noted above, in order to select from the aforementioned load types inthe illustrated embodiments, a number of load type criteria may bedefined. Furthermore, in the illustrated embodiment, at least some ofthese various load type criteria may be load weight dependent, such thatthe criteria vary with load weight.

It may be desirable, for example, to utilize linear equations of theform y=mx+b, where y is a threshold time or duration, x is the loadweight, m is the rate at which the threshold time or duration increasesas weight increases, and b is the y-intercept that best represents thedata at realistic load sizes. In some embodiments, the linear equationsmay be empirically determined, and in some embodiments, other equations,e.g., polynomial or non-linear equations, may be used to represent theload type criteria. In other embodiments, load type criteria may bebased on fuzzy logic or neural network-derived thresholds. Other mannersof mapping the determined times to different load types will beappreciated by those of ordinary skill having the benefit of the instantdisclosure.

In the illustrated embodiment, for example, six different load criteriamay be used to map the aforementioned sense, fill and peak times to thepolyester, mixed, cotton and towel load types. In this embodiment, thecriteria associated with the sense and fill times are based upon aduration from the start of dispensing water to the respective sense andfill times, and all are based on linear equations that are function ofthe dry weight of the load. An additional criterion associated with thepeak time, however, is based on a duration from the end of dispensingwater (or alternatively, the fill time) to the peak time, and is not afunction of the dry weight of the load, but is instead a constantthreshold.

A first load criterion that may be used is a polyester sense criterionthat may be used to determine when the sense time indicates that theload type is a polyester load type. In some embodiments, this criteriondefines a weight-varying threshold that is met when the sense time orduration is below the threshold.

A second load criterion that may be used is a towels sense criterionthat may be used to determine when the sense time indicates that theload type is a towels load type. In some embodiments, this criteriondefines a weight-varying threshold that is met when the sense time orduration is above the threshold.

A third load criterion that may be used is a cotton sense criterion thatmay be used to determine when the sense time indicates that the loadtype is a cotton load type. In some embodiments, this criterion definesa weight-varying threshold that is met when the sense time or durationis above the threshold, but still below the weight-varying threshold forthe towels sense criterion.

A fourth load criterion that may be used is a cotton peak criterion thatmay be used to determine when the peak time indicates that the load typeis a cotton load type. In some embodiments, this criterion defines aweight-independent threshold that is met when the peak time or durationis above the threshold, even when the cotton sense and towels sensecriteria are not met by the sense time or duration.

A fifth load criterion that may be used is a polyester fill criterionthat may be used to determine when the fill time indicates that the loadtype is a polyester load type. In some embodiments, this criteriondefines a weight-varying threshold that is met when the fill time orduration is below the threshold, even when the polyester sense criterionis not met by the sense time or duration.

Further, in some embodiments, a sixth load criterion may be used, andmay be referred to as a mixed sense criterion that is used to determinewhether to evaluate the cotton peak criterion or the polyester fillcriterion based upon whether the sense time is more indicative of acotton load type than a polyester load type. In some embodiments, thiscriterion defines a weight-varying threshold that, when the sense timeor duration is above the threshold, indicates that the peak time shouldbe evaluated against the cotton peak criterion to select between thecotton and mixed load types. In contrast, when the sense time orduration is below the threshold, the criterion indicates that the filltime should be evaluated against the polyester fill criterion to selectbetween the polyester and mixed load types. If none of the first fiveload criteria is met, then the load is determined to be a mixed loadtype.

It will be appreciated that the various criteria discussed herein may bedetermined empirically in some embodiments, and may be specific to aparticular laundry washing machine design. In addition, in someembodiments, additional factors may be considered in such criteria,e.g., water inlet flow rate, water temperature, etc.

FIG. 6 , for example, illustrates fluid level plots for three differentrepresentative loads during an initial fill operation, the first havinga polyester load type and represented using the subscript “P”, thesecond having a mixed load type and represented using the subscript “M”,and the third having a towels load type and represented using thesubscript “T”. Plots 140, 141 and 142 respectively represent theduration of the initial minimum fill, with each starting to fill thewash tub at time T₀, and plots 145, 146, and 147 respectively representthe fluid levels sensed by the fluid level sensor for each of thepolyester, mixed and towels loads. Times S_(P), S_(M) and S_(T)(represented by the circles) respectively represent the sense times forthe three loads, where the fluid level initially begins to rise. TimesF_(P), F_(M) and F_(T) (represented by the brackets) respectivelyrepresent the fill times for the three loads, where the predeterminedfluid level is reached. Times P_(P), P_(M) and P_(T) (represented by thediamonds) respectively represent the peak times for the three loads,where the fluid level stabilizes after the completion of the initialfill. It will be appreciated that since the towels load is generallymore absorbent than the mixed load, and the mixed load is generally moreabsorbent than the polyester load, the various sense, fill and peaktimes for the three loads reflect these absorbency differences.

Now turning to FIG. 7 , this figure illustrates another sequence ofoperations 150 that may be used to implement a wash cycle withabsorbency-based dynamic load type selection consistent with theinvention. Block 152 initially detects opening of the washing machinedoor, e.g., using door switch 86, and upon opening, block 154 determinesa tare weight assuming wash tub 16 is empty using weight sensor 62.

Block 156 then detects the door closing using door switch 86. Block 156may also check the output of weight sensor 62 to determine that a loadhas been placed in the wash tub. Block 158 then detects a selection bythe user of an “automatic” mode along with a request to start the washcycle, and then passes control to block 160 to initiate actuation ofdoor lock 88 to lock the door. A safety algorithm may also be performedat this time to determine whether the machine is able to proceed with awash cycle. At this time, the controller may also begin to slowly spinthe wash basket, particularly in the event that the weight sensor 62 isimplemented using an offset sensor that is sensitive to the distributionof a load in the wash tub (e.g., a single load cell disposed proximate acorner of the housing).

Next, block 162 determines the load weight using weight sensor 62 andthe tare weight determined in block 154, e.g., by averaging multipleweight sensor readings captured over the course of several revolutionsof the wash basket and then computing a difference between this loadedweight and the tare weight determined in block 154. At this time, it mayalso be desirable to use the load weight to calculate the variousweight-varying load type criteria thresholds discussed above.

Next, in block 164, water inlet 44 is controlled to start dispensingwater into the wash tub. It is generally desirable to distribute thewater evenly across the load, e.g., using multiple and/or oscillatingnozzles, and in some instances it may be desirable to continue spinningthe wash basket at a slow speed to further distribute the water moreevenly. In addition, a time may be started at this time to provide aconsistent point of reference for the time determinations.

As noted above, right after the water is turned on, pressure sensor 64will not detect any water at the bottom of the basket because of thefabric's absorptivity. Different fabrics have different absorptivitylevels (generally, from lowest to highest: delicates, polyester, mixed,cotton, towels). The fabric type and amount of fabric (e.g., asrepresented by weight) will both affect how much water is absorbed andhow long it takes for water to reach the bottom of the basket. Thus,once the pressure sensor detects a very small amount of water at thebottom of the basket representing a first detected change in fluid levelsensed by the fluid level sensor (block 166), the elapsed time betweenthis moment and the water inlet being opened to start dispensing wateris recorded as the sense time (block 168).

As noted above, in the illustrated embodiment, there are several caseswhere the sense time alone may be enough to determine the load type. Inparticular, there are three cases, based on the polyester sensecriterion, the cotton sense criterion and the towels sense criterion,where sense time is enough to decide the load type, and if any are met,then the rest of the sensing phase may be skipped and the load type maybe selected prior to reaching and recording the later times. In someinstances, the time savings may be several minutes or more, particularlyin the instance where a load contains only low absorbency fabrics andwater begins dropping to the bottom of the wash tub very soon afterwater dispensing starts. Thus, block 170 may determine if any of theaforementioned criteria are met, and if so, pass control to block 172 todetermine the load type based upon the sense time.

If not, however, block 170 passes control to block 174 to continuefilling the wash tub and wait until a predetermined fluid level, e.g., aminimum fill fluid level, is reached. Once this fluid level is reached,the water inlet is turned off (block 176) and the time elapsed betweenthis point and the water turning on is recorded as the fill time (block178). In the illustrated embodiment, filling to the minimal water levelmay be used to differentiate between polyester and mixed or mixed andcotton loads; however, fill time itself may be used to tell thedifference between polyester and mixed loads if the sense time alone isinsufficient to distinguish between the two. Thus, block 180 maydetermine if the fill time meets the polyester fill criterion, and ifso, passes control to block 172 and skip the remainder of the sensingphase.

If, however, the criterion is not met, block 180 passes control to block182 to wait for the fluid level to stabilize for a predeterminedstabilization duration (e.g., about 15 seconds in some embodiments). Asnoted above, once the water inlet is stopped, the water level willcontinue to increase as water drips from the load. These small waterlevel changes may be sensed by the pressure sensor, and once the waterlevel has stagnated or stabilized for the desired duration, the timeelapsed between the water being shut off and the last increase inpressure sensor readings may be recorded as the peak time in block 184.

Next, control passes to block 172 to determine the load type based onthe three recorded times. Then, in block 186, the controller mayconfigure the wash cycle based on the load type, and may optionallydisplay these settings to a user on a display of the machine. Block 188optionally dispenses an additional amount of water to complete the fillphase (e.g., if based upon the weight and/or load type it is determinedthat a larger volume of water is required). The wash cycle is thencompleted in block 190 using the operational settings associated withthe selected load type, and upon completion of the wash cycle, the dooris unlocked in block 192 by deactivating door lock 88.

While it will be appreciated that dynamic load type selection based uponthe aforementioned times may be implemented in a number of othermanners, one example implementation of a load type selection operationsuch as is performed in block 172 is illustrated by sequence ofoperations 200 in FIG. 8 . In general, in the illustrated embodiment,the load weight and the sense time may be used to categorize a load intoone of five categories:

1) Known to be polyester from sense time

2) Cannot tell between polyester and mixed, needs fill time to decide

3) Cannot tell between mixed and cotton, needs peak time to decide

4) Known to be cotton from sense time.

5) Known to be towels from sense time.

Thus, sequence 200 may be used to use the sense time, and if necessary,either of the fill and peak times, in order to determine the load type.Furthermore, sequence 200 may, in some instances, select a load typeprior to reaching the fill and/or peak times, thereby dynamicallyshortening a sensing phase during which the load type is determined.

As shown in block 202, sequence 200 may begin by calculating the sensetime, and then determining in block 204 (e.g., using the polyester sensecriterion) whether the sense time is low enough for the polyester loadtype. If so, control passes to block 206 to skip the fill and peak timecalculations and select the polyester load type.

Otherwise, block 204 passes control to block 208 to determine (e.g.,using the towels sense criterion) whether the sense time is high enoughfor the towels load type. If so, control passes to block 210 to skip thefill and peak time calculations and select the towels load type.

Otherwise, block 208 passes control to block 214 to determine (e.g.,using the cotton sense criterion) whether the sense time is high enoughfor the cotton load type, or more specifically, if the sense time is toohigh for the mixed load type but too low for the towels load type. Ifso, control passes to block 216 to skip the fill and peak timecalculations and select the cotton load type.

Otherwise, block 214 passes control to block 218 to calculate the filltime, and block 220 determines (e.g., using the mixed sense criterion)whether to evaluate the cotton peak criterion or the polyester fillcriterion based upon whether the sense time is more indicative of acotton load type than a polyester load type. Specifically, if block 220determines that the sense time is in range of a polyester or mixed loadtype, control passes to block 222 to determine (e.g., using thepolyester fill criterion) whether the fill time is above or below thecalculated threshold associated with the criterion. If below, controlpasses to block 224 to skip the peak time calculation and select thepolyester load type, and if above, control passes to block 226 to skipthe peak time calculation and select the mixed load type.

Returning to block 220, if it is determined that the sense time is notin range of a polyester or mixed load type, control passes to block 228to calculate the peak time, and then to block 230 to determine (e.g.,using the peak cotton criterion) whether the peak time is above or belowthe calculated threshold associated with the criterion. If above,control passes to block 232 to select the cotton load type, and ifbelow, control passes to block 234 to select the mixed load type.

It will be appreciated that sequences 150 and 200 are merelyillustrative in nature, and that other sequences may be used in otherembodiments. Further, different numbers of load types and criteria usedto distinguish between load types may be used in other embodiments.

Load Type Selection Based on Color Composition Analysis During Loading

As noted above, in addition to or in lieu of load type selection basedupon absorption characteristics of a load, the color composition of aload may be used. In some embodiments consistent with the invention, forexample, the colors of the articles in a load may be detected and usedto characterize the load, e.g., to categorized the load into one of aplurality of different color-based load types. The color-based loadtypes, for example, may include load types such as whites, lights,darks, reds, etc. The load types may, in some embodiments, include solidcolor load types that are associated with specific colors or ranges ofcolors, e.g., whites, lights, darks, reds, and in some embodiments, theload types may include mixed color load types that are associated withmixtures of two or more solid color load types, e.g., mixed lights andwhites, mixed lights and darks, mixed darks and reds, etc. Then, basedupon the selected color-based load type, whether considered alone or incombination with an absorption-based load type, one or more operationalsettings may be set for a wash cycle performed by a laundry washingmachine, which can, in many instances, improve the lifetime of articles,whose lifetimes are often shortened due to non-ideal washingenvironments.

In some embodiments, and as will be discussed in greater detail below,it may be desirable to utilize a color detection sensor in combinationwith a weight sensor, and optionally a door switch, to perform aplurality of color composition data captures with the color detectionsensor responsive to detected weight changes sensed by the weight sensoras a load of articles is added to a wash tub. Color composition datacaptures, e.g., in the form of digital images comprising arrays of pixeldata, may be triggered, for example, in response to the weight sensordetecting a stable weight in the wash tub for at least a predeterminedduration. The detection of a stable weight for at least a predeterminedduration may be associated with, for example, the addition of a newarticle (or articles) to the wash tub, thereby enabling a new image tobe captured for each article, or set of articles, added to the wash tub.As such, the amount of weight change, as well as the predeterminedduration, may be empirically determined in some embodiments to optimizethe capture of color composition data based upon how users generally addarticles to a wash tub.

Moreover, the determination of a stable weight may vary in differentembodiments. For example, in some embodiments, a stable weight may bebased on an amount of weight change over the predetermined duration thatvaries by less than a threshold amount or percentage. In someembodiments, a stable weight may be based on a variation of less thanabout 0.5 pounds over about a 2 second duration, although it will beappreciated that the invention is not limited to these particularvalues, as other values may be better suited for other laundry washingmachine designs or even different users.

In addition, in some embodiments, it may be desirable to utilize a colordecision algorithm to characterize captured color composition data inassociation with characterizing a load of articles. A color decisionalgorithm, in this regard, may be considered to include acomputer-implemented algorithm capable of processing color compositiondata collected from a load in order to characterize the color or colorsof the articles in the load. A color decision algorithm in someembodiments may be performed or executed entirely within a laundrywashing machine, e.g., by the controller thereof, or may be performed orexecuted entirely within a device that is remove from the laundrywashing machine, e.g., on a cloud computing device, a mobile device, aserver, or practically any type of computing device that may be incommunication with the laundry washing machine, whereby the laundrywashing machine may initiate the color decisional algorithm bycommunicating captured color composition data to a remote device andreceiving result data from the remote device containing intermediate orfinal results associated with the color decision algorithm. In stillother embodiments, different portions of a color decision algorithm maybe performed or executed by a laundry washing machine in combinationwith one or more remote devices, with various input and/or result datacommunicated therebetween.

A color decision algorithm in some embodiments may operate at least inpart by assigning color categories to pixels in captured colorcomposition data. For example, where captured color composition datatakes the form of a series of captured images, color categories may beassigned to all or at least a subset of the pixels in each capturedimage, and a color decision algorithm may characterize a load in part bycounting the number of pixels assigned to each color category. It may bedesirable in some embodiments to exclude pixels associated with certainregions of an image, e.g., if certain regions of the field of view of acolor detection sensor do not depict the load itself, e.g., if certainregions represent the structure of the laundry washing machine itself.In some embodiments, for example, pixels that are determined tocorrespond to the wash tub itself may be excluded, or may be assigned toa “wash tub” category. Determination of whether pixels correspond to thewash tub may be based, for example, on a known color of the wash tub,or, for example, by comparison of an image with a captured image of anempty wash tub.

It will also be appreciated that the pixels to which color categoriesare assigned may, but are not required to, correspond to the pixels ineach capture of color composition data. In other embodiments, however,the sizes (i.e., the regions within the field of view of the colordetection sensor to which each pixel corresponds) may vary between theraw data captured by the color detection sensor and the colorcomposition data that is analyzed by a color decision algorithm. As anexample, the pixels used for color categories may represent groups ofpixels in captured images in some embodiments, e.g., as a result ofdownsampling of the captured images to reduce the volume of colorcomposition data processed by the color decision algorithm.

In addition, in some embodiments, once color categories are assigned topixels from the color composition data, the counts of the pixels in eachcategory may be used to characterize the overall load, e.g., to assign acolor category to the load itself, such as whites, lights, darks, reds,or mixes thereof. In other embodiments, however, a color category neednot be assigned to the load itself, and the color categories of thecolor composition data may be analyzed separate of any overall loadcharacterization in order to control one or more operational settingsfor a wash cycle.

As will also become more apparent below, a color decision algorithm mayalso be used to detect outlier articles in a load, and to optionallygenerate an alert to a user and/or change one or more operationalsettings for a wash cycle based upon detection of outlier articles. Anoutlier article, in this regard, may be considered to be an article thatsubstantially differs in color composition from other articles in aload, e.g., a white article in a load that is predominantly full of darkand/or red articles, or vice versa. It will be appreciated that thepresence of an outlier article in a load may increase the likelihood ofbleeding between articles during washing, e.g., if a single red or darkarticle (or a few of such articles) is included in a load of whites, orif a single white article (or a few of such articles) is included in aload of darks or reds.

In some embodiments, the detection of an outlier article may be used togenerate an alert in response to detection of one or more outlierarticles from the load of articles added to the wash tub in thecategorized color composition data. An alert, for example, may beimplemented using an audible and/or visual indication to the user, suchas a light indicator on a user interface of the laundry washing machine,a pop-up window on an LCD screen, an audible warning such as a buzzer orbeep, and/or an alert generated on a connected mobile device (e.g., atext message, a notification, etc.), and in some instances, the alertmay be combined with a mandated pause in the wash cycle to give the userthe opportunity to remove any outlier articles. In some embodiments, forexample, a user may be given an opportunity to remove any outlierarticles and thereafter may be required to confirm that the articleshave been removed before the wash cycle may proceed.

Further, in some embodiments, instead of or in addition to thegeneration of an alert, one or more operational settings for a washcycle may be modified in part based on the detected presence of one ormore outlier articles. For example, in some embodiments, the detectedpresence of an outlier article may cause a color decision algorithm toselect a different color load type for a load than would have beenselected were the outlier article not detected, e.g., by changing asolid color load type to a mixed color load type.

A color decision algorithm may also be based in part on some calibrationperformed during installation and/or during each wash cycle. Forexample, in some embodiments, ambient room lighting conditions may beassessed just after a color detection sensor has been activated, e.g.,to compare images from a calibration process (e.g., the calibrationprocess discussed in greater detail below) with one or more currentimages in order to process the images by providing R, B and/or G gainsor subtractions to the image/video data captured by a color decisionalgorithm. In addition, it will be appreciated that various imageprocessing techniques may be used in connection with a color decisionalgorithm, e.g., to crop or smooth an image, etc.

Now turning to FIGS. 9A-9C, these figures illustrate an example sequenceof operations 250 for capturing and analyzing color composition data fora load in a manner consistent with some embodiments of the invention.Sequence 250 utilizes as a color detection sensor a digital camera, aswell as a door switch and a weight sensor such as a load cell, tocapture digital images of articles of a load as they are loaded into alaundry washing machine. Sequence 250 is initiated in block 252 upondetection of the door being opened by the door switch, and block 254captures a weight reading from the load cell to obtain a tare valuecorresponding to the weight of the empty wash tub. Next, in block 256,the camera is initialized, and if one or more lights are used toilluminate the wash tub and assist with capturing images, those lightsmay be turned on at this time.

Next, in block 258, a sleep timer, which may be used to place thelaundry washing machine in a low power mode in the absence of activityfor a predetermined period of time, is started, and block 260 determineswhether the door has been closed. If not, block 262 determines whetherthe sleep timer has expired.

If the sleep timer has not yet expired, control passes to block 264 tocapture a current weight value from the load cell, and block 266determines whether any article removal has been detected, e.g., if theweight change is a negative value from the previously captured weightvalue. If not, control passes to block 268 to determine if a weightchange from the previously captured weight value is greater than afirst, article addition weight constant. The article addition weightconstant may be selected, for example, based upon a value that isindicative of the weight of one or more articles typically added to awash tub, with the understanding that a lower constant will generallyresult in the capture of more images representing different layers ofthe load during the loading phase, while a higher constant will resultin the capture of fewer images representing different layers of the loadduring the loading phase.

If the change in weight is greater than the article addition weightconstant, control passes to block 270 to start a stability timer andsave the current weight as a stability weight, and then return controlto block 258 to reset the sleep timer and continue monitoring theweight. As noted above, in the illustrated embodiment images aregenerally captured after the weight in the wash tub has remainedgenerally stable for a predetermined duration (e.g., about 2 seconds inthe illustrated embodiment), as such, the stability timer is started towait for the predetermined duration and trigger an image capture if theweight remains stable over this duration. The determination of whetherthe weight has remained stable may be made based upon comparison of thecurrent weight against a relatively smaller constant referred to hereinas a stability weight constant (e.g., about 0.5 pounds in theillustrated embodiment). As such, block 272, which is executed if block268 determines that the weight change is less than the article additionweight constant, is used to compare the weight change against thisstability weight constant whenever the stability timer is running, andpasses control to block 270 in the event that the weight change duringthis duration exceeds the stability weight constant. Doing so resets thestability timer and saves the current weight as the new stabilityweight.

If the stability weight constant has not been exceeded in block 272,control passes to block 274 to determine if the stability timer hasexpired. If not, control returns to block 272 to continue to wait forthe stability timer to expire. If the stability timer has expired,however, block 274 passes control to block 276 to capture colorcomposition data (e.g., an image, a series of images, or a video) andrecord the current weight, which is then used as the baseline weightagainst which the article addition weight constant is subsequentlymeasured. The capture of color composition data may also, in someinstances, be accompanied by a determination of when the data has becomestable, e.g., when a series of images or frames of video depictsubstantially the same image. In some embodiments, for example, when itis desirable to capture color composition data, a sequence of images orframes of a video stream may be captured and compared with one anotheruntil image stability is reached, e.g., where no movement of additionalclothing being added to the wash tub or a user's arm is detected. Whenimage stability is achieved, it may be used as a precursor to stop thestream of image captures or video, record a stable capture, and weighthe load and wait on a further change in state, e.g., someone puttingmore clothes in the basket, closing the door, touching the userinterface, etc.

After capturing color composition data in block 276, control returns toblock 258 to reset the sleep timer and continue monitoring the weight.Returning to block 266, if article removal is detected, e.g., as aresult of a negative weight change being detected, control passes toblock 278 to delete the previously-stored image, and record the weight,and then return control to block 258.

Now returning to block 262, and with further reference to FIG. 9B, inthe event that the sleep timer expires, control passes to block 280 seta sleep state to TRUE, and then to block 282 to turn off the camera andany lights. Block 284 then sets a sleep weight using the current weight,and block 286 turns off the display of the laundry washing machine,whereby the laundry washing machine is in a sleep state.

Blocks 288, 290 and 292 test for various conditions that can awaken thelaundry washing machine from the sleep state. Block 288 tests for aweight change that is greater than a second weight constant, whileblocks 290 and 292 test for whether a user control has been actuated(e.g., for a touch screen embodiment, whether the screen has beentouched by the user) or whether the door has been closed by the user(sensed by the door switch). If block 288 detects a sufficient weightchange relative to the second weight constant (which may be equal toeither the stability weight constant or the article addition weightconstant, or another constant altogether), control passes to block 294to capture color composition data from the wash tub (e.g., one or moreimages and/or a video) and record the weight, and generally with thecolor composition capture occurring once image stability has beendetected. Control then passes to block 296 to turn on the display and toblock 298 to set the sleep state to FALSE, and control then returns toblock 256 of FIG. 9A. If blocks 290 and 292 detect either actuation of auser control or closing of the door, block 294 is bypassed, and controlpasses directly to blocks 296 and 298 to turn on the display, set thesleep state to FALSE and awaken the laundry washing machine, and thenreturn control to block 256 of FIG. 9A.

Returning to block 260 of FIG. 9A, and with further reference to FIG.9C, if closing of the door is detected with the door switch, controlpasses to block 300 of FIG. 9C to determine if the current weight isgreater than a third weight constant (which may be the same or differentfrom any of the aforementioned constants), and if so, passes control toblock 302 to capture color composition data from the wash tub (e.g., oneor more images and/or a video), and generally with the color compositioncapture occurring once image stability has been detected. If the currentweight does not exceed the third weight constant, block 300 bypassesblock 302 and no additional color composition data is captured.

In either event, block 304 next analyzes all of the captured colorcomposition data (e.g., images and/or video) using a color decisionalgorithm, which may be performed locally in the laundry washing machinecontroller, remotely in a remote device, or using a combination thereof.The results of the algorithm are then returned in block 306. Inaddition, as illustrated in block 308, if at any time prior toinitiation of the initial fill for the wash cycle opening of the door isdetected using the door switch and the addition of other articles isdetected using the weight sensor, control may pass to block 310 tocapture additional color composition data (e.g., one or more imagesand/or a video), and generally with the color composition captureoccurring once image stability has been detected. Control the returns toblock 304 to reanalyze all of the color composition data and potentiallyrecharacterize the load based upon the new color composition data.

Now turning to FIGS. 10A-10B, one example sequence of operations 320suitable for implementing a color decision algorithm consistent withsome embodiments of the invention is illustrated. In particular, in oneembodiment consistent with the invention, and as illustrated in block322, the pixels in each captured image may be analyzed and each assignedor classified into one of a plurality of color categories, e.g., awhites category, a lights category, a darks category, a reds categoryand a “wash tub” category (representing a pixel that is associated withthe structure of the wash tub itself (e.g., the wash tub and/or any washbasket, or any agitator therein, and then the number of pixels assignedto each color category may be determined and used to characterize theoverall load. The categorization may be performed, for example, usingone or more color categorization criteria that define the membership ofa pixel within a particular color category, and against which the colorcomposition data for the pixel may be tested, e.g., based on brightnessand/or color cast, individual color intensities, hue, lightness and/orother imaging data.

In one example embodiment, thresholds may be used to categorize a loadbased upon the numbers of pixels assigned to each color category, e.g.,using a whites threshold, a lights threshold, a darks threshold and areds threshold that, when exceeded, indicates that the load ispredominantly of that color load type. The thresholds may be based onpixel counts in some embodiments, or based on other criteria, e.g.,percentages, in other embodiments. In addition, as will be discussed ingreater detail below, thresholds may also be used to identify outlierarticles and trigger the generation of alerts and/or changing the loadtype to a different load type, e.g., a mixed load type, whenever pixelsassociated with an outlier article exceed a particular threshold.

Thus, for example, block 324 may first determine whether the capturedimages show only an empty wash tub, i.e., where all or a predominantnumber of pixels are assigned to a wash tub category. If so, controlpasses to block 326, and an empty wash tub result is returned.

If not, block 328 initiates a decision tree that selects various resultsprimarily based upon which among the different color categories is mostrepresented in the categorized pixels. In particular, block 328determines whether whites represent the most pixels, and if so, passescontrol to block 330 to test whether the number or percentage of whitespixels exceeds a first whites threshold. If so, control passes to block332 to return a whites color load type. If not, however, control passesto block 334 to generate an article alert that indicates to the userthat the whites load is mixed with one or more non-white articles.Control then passes to block 336 to determine if the whites pixelsexceed a second whites threshold, which is generally lower than thefirst whites threshold. If so, control passes to block 332 to return awhites color load type; however, if not, control instead passes to block338 to instead return a lights color load type, thereby automaticallyselecting a different load type from the whites load type as a result ofthe detection of the outlier article(s).

Returning to block 328, if whites does not represent the most pixels,control passes to block 340 to determine whether lights represent themost pixels, and if so, passes control to block 342 to test whether thenumber or percentage of white pixels exceeds a lights threshold. If so,control passes to block 338 to return a lights color load type. If not,however, control passes to block 344 to generate an article alert thatindicates to the user that the lights load is mixed with one or morenon-lights articles. Control then passes to block 338 to return thelights color load type.

Returning to block 340, if lights does not represent the most pixels,control passes to block 346 to determine whether darks represent themost pixels, and if so, passes control to block 348 to test whether thenumber or percentage of darks pixels exceeds a first darks threshold. Ifso, control passes to block 350 to test whether the number or percentageof reds pixels exceeds a reds threshold, and if so, passes control toblock 352 to return a reds color load type. If not, however, controlpasses to block 354 to return a darks color load type.

Returning to block 348, if the first darks threshold is not met, controlpasses to block 356 to generate an article alert that indicates to theuser that the darks load is mixed with one or more non-darks articles.Control then passes to block 358 to determine if the darks pixels exceeda second darks threshold, which is generally lower than the first darksthreshold. If so, control passes to block 354 to return a darks colorload type; however, if not, control instead passes to block 360 toinstead return a lights color load type, thereby automatically selectinga different load type from the darks load type as a result of thedetection of the outlier article(s).

Returning to block 346, if darks does not represent the most pixels(indicating that no one color category is predominant), control passesto block 362 to generate an article alert that indicates to the userthat the load is a mixed load. Control then passes to block 360 toreturn a lights color load type.

It will be appreciated that various numbers and combinations of colorcategories, thresholds, category criteria, etc. may be used in variousembodiments. In addition, other types of sensors may be used inconnection with color composition characterization, e.g., using multipleload cells or other weight sensors, using other color detection sensors,omitting or using various types of lights, using image analysis ratherthan weight to sense articles after being added to a wash tub, using aproximity sensor to wake up from a sleep state, etc.

Further, implementation of a color decision algorithm may vary indifferent embodiments, with characteristics of the algorithm determinedempirically in some embodiments, and based on various criteria,threshold, etc. Furthermore, it will be appreciated that trained machinelearning models may be used in some embodiments to characterize pixels,characterize loads and/or identify outlier articles. Therefore, theinvention is not limited to the specific algorithm implementationsdiscussed herein.

Moreover, it will be appreciated that the generation of article alertsand/or the selection of alternate color load types or otherwisemodifying operational settings to account for detected outlier articlesmay be implemented in various manners. Generally, the detection of theoutlier articles may be performed during a loading phase of the washcycle, and concurrently with the categorization of a load, and thus forboth categorization and outlier article detection, it may be desirablein some embodiments to instruct or educate a user to add articlesprogressively to the wash tub, rather than add the entire load at once,thereby enabling additional images of the load to be captured, andincreasing the amount of color composition data available for analysis.

Further, it should be appreciated that the generation of article alertsand/or the selection of alternate color load types or otherwisemodifying operational settings to account for detected outlier articlesmay be based in part on the aforementioned failure to meet certainthresholds associated with particular color categories, even when amajority of pixels is associated with those particular color categories.In other embodiments, however, separate criteria may be used to detectoutlier articles, e.g., by determining when the number of pixelsassigned to a particular color category exceeds a threshold when thenumber of pixels assigned to a different color category also exceedssome threshold (or, in some cases, is still determined to be the colorcategory having the greatest number of assigned pixels). Other mannersof detecting the presence of outlier articles based on counts of pixelassignments will be appreciated by those of ordinary skill having thebenefit of the instant disclosure, so the invention is not limited tothe specific detection criteria disclosed herein.

Laundry Washing Machine Calibration

It will next be appreciated that the aforementioned absorption-based andcolor-based load categorization functionality may be based on variousfactors that can vary from installation to installation of a laundrywashing machine. For the absorption-based load categorizationfunctionality described herein, for example, it may be desirable tocorrect for the actual water pressure of a water supply to which thelaundry washing machine is connected, particularly where a fluid levelsensor, rather than a flow sensor, is used to determine the amount ofwater added to a wash tub, as the water pressure of the water supply canaffect the amount of time it takes to reach a predetermined fill level.It therefore may be desirable to perform a calibration process in someembodiments to generate a calibration factor associated with the waterpressure of the water supply that may be used to correct for waterpressure variations in different installations. As will become moreapparent below, a calibration process in some embodiments may includecontrolling a water inlet to dispense water into a wash tub while thewash tub is empty and determining a time to reach a predetermined fluidlevel in the wash tub, and optionally repeating the fill multiple timesand averaging the results. From the calculated time, a water pressuremay be determined and used in the aforementioned absorption-basedcharacterization of a load.

For the color-based load characterization functionality describedherein, it may be desirable to correct for ambient lighting conditionswithin the vicinity of a laundry washing machine, which may be used, forexample, to set the various criteria used to assign pixels in capturedcolor composition data to various color categories. It will beappreciated, for example, that a laundry washing machine installed in adark closet or basement and/or using relatively dim and warm lightingwill present a substantially different surrounding environment than alaundry washing machine installed in a laundry room that is brightly-litwith cool color temperature lighting (as, for example, light coloredarticles would generally appear darker in a dark closet than if in abright laundry room), and as such, by calibrating the color detectionsensor to account for the actual ambient lighting conditions may resultin more consistent color categorization from machine to machine.

In addition, for one or both of absorption-based and color-based loadcharacterization, it may be desirable to additionally correct for washtub weight, e.g., by sensing a tare weight value for the wash tub whilethe wash tub is empty. In particular, when a weight sensor isimplemented as a load cell that is offset from an axis of rotation of awash basket in the wash tub, it may be desirable to compensate for anymanufacturing variations and capture multiple weight readings duringrotation of the wash basket in the wash tub and while the wash tub isempty for use as an empty wash tub weight, which can not only be usedfor sensing the weight of the overall load, but also can be used todetect whether or not a laundry washing machine is actually empty atstartup.

In each of these instances, the calibration factors generated as aresult of the calibration processes may be used subsequently in thecontrol over a wash cycle, e.g., by setting one or more operationalsettings for the wash cycle. Further, while the hereinafter-describedcalibration process includes all three of the aforementionedcalibrations, it will be appreciated that each of the calibrations maybe performed separately in different embodiments, so the invention isnot limited to a calibration process that performs all threecalibrations. Moreover, while the herein-described calibration processis described as being performed after the initial installation of alaundry washing machine, it will be appreciated that any of theaforementioned calibrations may also be performed later throughout thelifetime of a laundry washing machine, e.g., on a preprogrammed scheduleor in response to manual user or service personnel instruction. Further,some calibration operations may be performed at the start of anindividual wash cycle in some embodiments, e.g., to capture images atthe initial warm up of a color detection sensor upon the opening of adoor of a laundry washing machine.

Now turning to FIGS. 11A-11C, these figures illustrate an examplesequence of operations 400 for performing a calibration operation on alaundry washing machine consistent with some embodiments of theinvention. Sequence 400, for example, may be initiated upon power on ofthe laundry washing machine, as illustrated in block 402, and may, forexample, use a user interface such as a touch-screen display to bothinstruct a user and receive user input at various points in the process.In block 404, for example, the user may be requested to user confirmthat the physical installation is complete and that the machine is readyto be calibrated and used, e.g., confirming that the machine is in itsdesired location. In some embodiments, a user may also be requested toconfirm that the machine is connected to the water supply and drain.

Next, in block 406, the user may be instructed to open the door to thelaundry washing machine and confirm that the ambient lighting is normalfor the installation location. Then, in block 408, upon detecting thedoor open, the camera or other color detection sensor may be initializedand (if used) any lights may be turned on, and in block 410 one or moreimages of the empty wash tub may be captured. In addition, in someembodiments, it may be desirable to instruct a user to vary lightingconditions and capture images in these varying lighting conditions,e.g., to cover the range of lighting conditions that may be experiencedduring the normal course of use of the laundry washing machine.

From the one or more images, an average brightness and/or other lightparameters may be determined from the images in block 412, and in block414 the average brightness and/or other light parameters such as averagecolor cast may be used to calibrate the color-based characterizationprocess, e.g., to effectively adjust the response of a color decisionalgorithm. In some embodiments, for example, correction values may bedetermined in each of the red, green and blue space, and colorcomposition data captured during subsequent wash cycles may be adjustedusing these correction values. The adjusted color composition data maythen be compared against thresholds assigned to different colorcategories (e.g., thresholds based on average brightness of color). Insome embodiments, for example, color composition data may be capturedand parameters of ambient light may be measured based on the averagecolor of the captured data. The categories may then be adjusted based onthe brightness of the lighting, which may shift ranges assigned todifferent categories based on such adjustments. Color cast removal mayalso be performed with parameter settings of the color detection sensorand image analysis in some embodiments.

In some embodiments, in addition to or in lieu of adjusting the colorcomposition data itself, the various color categorization criteria orthresholds used to categorize a load may be adjusted based oncalibration to effectively adjust the response of the color decisionalgorithm. In one embodiment, for example, color categories may bediscriminated between one another based on thresholds of brightnessand/or color cast, and an average brightness and/or color castdetermined during the calibration process may be used to adjust thesethresholds. Other manners of adjusting the response of a color decisionalgorithm based upon calibration data collected from ambient lightingconditions may be used in other embodiments, as will be appreciated bythose of ordinary skill in the art having the benefit of the instantdisclosure.

Next, turning to FIG. 11B, after calibrating for ambient lightconditions, control may pass to block 416 to perform a calibrationprocess for water supply pressure. In particular, block 416 may causethe laundry washing machine to turn on the water inlet to fill to apredetermined level and then perform a drain cycle to empty the washtub. Doing so enables excess air to be removed from the pump and tubingthat could otherwise impact the calibration process.

Next, in block 418, another fill operation commences and a timer isstarted to determine the time required to reach a predetermined level inthe wash tub as sensed by the fluid level sensor. Once thatpredetermined level is sensed, block 420 stops the fill and stops thetimer, and additionally records the elapsed time, and block 422completes a drain cycle to drain the water from the wash tub. Block 424then returns control to block 418 to repeat this process for a pluralityof iterations (e.g., 3-7 in the illustrated embodiment), and once thedesired number of iterations have been completed, block 426 averages therecorded times and calculates a water supply pressure therefrom.

While a water supply pressure may be calculated from the elapsed timesin a number of manners, in one embodiment the water supply pressure maybe calculated using the formula:

${\lim\limits_{x\rightarrow n}P} = {{{psiLevel}(x)} + b}$where P is the pressure of the water supply, psiLevel is the function inwhich time x grows with water level, and b is the y intercept. psiLevelin some embodiments may be determined empirically for a particularlaundry washing machine design.

In some embodiments, a precise water pressure may not be required, andinstead a series of thresholds may be used to determine a water pressurerange, e.g., to the nearest 1 psi or nearest 5 psi. Thus, if the averageelapsed time is below a first threshold, this may signify a waterpressure of about 40 psi, while being below a second threshold maysignify a water pressure of about 35 psi, while being below a thirdthreshold may signify a water pressure of about 30 psi, etc.

Once the water pressure is determined the water pressure may be used tocalculate a set of absorption correction factors in block 428. Forexample, in the embodiment described above, measured sense, fill andpeak times are used to characterize a load, and complementary sense,fill and peak calibration factors may be calculated for use with thesemeasured times. In one example embodiment, each calibration factor maytake the form of a logarithmic line, e.g., y=m*In(x)+b, where yrepresents a calibration factor for one of the sense, fill and peak timevariables, m represents the rate at which it is increased, x representsthe measured water pressure, and b represents a y intercept of thefunction, resulting in three calibration factors as illustrated below:Sense calibration factor=a*In(waterPressure)+xFill calibration factor=b*In(waterPressure)+yPeak calibration factor=c*In(waterPressure)+z

It will be appreciated that these calibration factors may be applied tothe measured sense, fill and peak times in some embodiments, or mayalternatively be applied to the thresholds that are used to discriminatebetween different load types. It will also be appreciated that thecalibration factors may be empirically determined in some embodiments,and in some embodiments, other equations, e.g., polynomial, linear orother types of non-linear equations may be used to represent thecalibration factors. In other embodiments, calibration factors may bebased on fuzzy logic or neural network-derived values. Other manners ofmapping the average elapsed time to water pressure and/or water pressureto calibration factors will be appreciated by those of ordinary skillhaving the benefit of the instant disclosure, and further it will beappreciated that average elapsed time may be mapped directly tocalibration factors without explicitly calculating a water pressure insome embodiments.

Next, turning to FIG. 11C, after calibrating for water pressure, controlmay pass to block 430 to perform a calibration process for wash tubweight. As noted above, in some embodiments a single load cell offsetfrom a rotational axis of the wash basket may be used to sense weight,and thus, it is possible for the weight sensed by the load cell to varywith the rotational position of any components within the wash basket.As such, it may be desirable in some embodiments to spin or rotate thewash basket while sensing weight and average the results in order toobtain a rotational position-invariant tare value.

In particular, block 430 may cause the wash basket in the wash tub toslowly spin using the drive system, and block 432 may wait for a steadystate speed to be reached. Once that steady state speed has beenreached, block 434 may collect multiple load cell readings over apredetermined time span and calculate an average thereof. Block 436 maythen stop the drive system and save the calculated average as a tarevalue corresponding to the weight of the empty wash tub.

Thereafter, block 438 may notify the user of the completion of thecalibration process, and block 440 may set the laundry washing machineto a “normal operation” state, indicating that the laundry washingmachine is ready for normal service.

It will be appreciated that it may also be desirable to run one or moreof the aforementioned calibrations at a later time during the lifetimeof the laundry washing machine, and that in particular it may bedesirable to periodically perform weight sensor calibration on arelatively frequent basis, e.g., prior to every wash cycle in someembodiments, to check whether the weight of the wash tub has beenaffected by any orientation change.

Various additional modifications may be made to the illustratedembodiments consistent with the invention. Therefore, the invention liesin the claims hereinafter appended.

What is claimed is:
 1. A laundry washing machine, comprising: a wash tubdisposed within a housing; a color detection sensor positioned tocapture color composition data of a load of articles as the load ofarticles is added to the wash tub; a weight sensor operatively coupledto the wash tub to sense a weight of the load of articles as the load ofarticles is added to the wash tub; and a controller coupled to the colordetection sensor and the weight sensor and configured to initiate aplurality of color composition data captures with the color detectionsensor responsive to detected weight changes sensed by the weight sensoras the load of articles is added to the wash tub, the controllerconfigured to initiate each color composition data capture in responseat least in part to the weight sensor detecting a stable weight in thewash tub for at least a predetermined duration, wherein thepredetermined duration is selected to optimize color composition datacapture based upon how users add articles to a wash tub; wherein thecontroller is further configured to set one or more operational settingsfor a wash cycle based upon the plurality of color composition datacaptures.
 2. The laundry washing machine of claim 1, wherein theplurality of color composition data captures includes a first colorcomposition data capture performed before a second color compositiondata capture, and wherein the controller is configured to, for thesecond color composition data capture, detect the stable weight for atleast the predetermined duration by determining that a weight changesensed by the weight sensor during the predetermined duration is lessthan a stability weight constant.
 3. The laundry washing machine ofclaim 2, wherein the controller is configured to, for the second colorcomposition data capture, detect the stable weight for at least thepredetermined duration by starting a stability timer when a weightchange detected subsequent to the first composition data capture isgreater than an article addition weight constant.
 4. The laundry washingmachine of claim 3, wherein the controller is configured to, for thesecond color composition data capture, store a stability weight inconnection with starting the stability timer, and reset the stabilitytimer and update the stability weight if the weight change sensed by theweight sensor during the predetermined duration exceeds the stabilityweight constant.
 5. The laundry washing machine of claim 4, wherein thecontroller is configured to, for the second color composition datacapture, initiate the second color composition data capture in responseto the stability timer reaching the predetermined duration.
 6. Thelaundry washing machine of claim 1, wherein the controller is furtherconfigured to detect removal of an article from the wash tub using theweight sensor and delete a color composition data capture in response todetecting removal of the article.
 7. The laundry washing machine ofclaim 1, wherein the controller is further configured to initiate eachcolor composition data capture in response at least in part to detectionof image stability in the wash tub.
 8. The laundry washing machine ofclaim 1, wherein the controller is configured to initiate the pluralityof color composition data captures in response to detecting an opendoor, and to determine that all articles in the load have been added tothe wash tub in response to detecting a closed door.
 9. The laundrywashing machine of claim 8, wherein the controller is configured toinitiate an additional capture of color composition data after detectingthe closed door if a weight sensed by the weight sensor is greater thana predetermined constant.
 10. The laundry washing machine of claim 8,wherein the controller is further configured to initiate a capture of anadditional color composition data capture after detecting the closeddoor in response to detecting that the door has been reopened and thatthe weight sensor has detected another article added to the wash tub.11. The laundry washing machine of claim 8, wherein the controller isconfigured to start a sleep timer in response to detecting the opendoor, to reset the sleep timer in connection with each color compositiondata capture, to put the laundry washing machine in a sleep state inresponse to expiration of the sleep timer, and to awaken the laundrywashing machine and initiate a color composition data capture inresponse to detection of a weight change by the weight sensor while thelaundry washing machine is in the sleep state.
 12. The laundry washingmachine of claim 1, wherein the color detection sensor comprises animage sensor configured to capture a digital image, and wherein thelaundry washing machine further comprises a light positioned toilluminate the wash tub during image capture with the image sensor. 13.The laundry washing machine of claim 1, wherein the controller isfurther configured to initiate a color decision algorithm tocharacterize the captured color composition data by assigning each of aplurality of pixels in the captured color composition data to one of aplurality of color categories, and to characterize the load of articlesbased upon the characterized color composition data, and to set one ormore operational settings for a wash cycle based upon thecharacterization of the load of articles by the color decisionalgorithm.
 14. The laundry washing machine of claim 13, wherein thecontroller is configured to initiate the color decision algorithm byexecuting at least a portion of the color decision algorithm.
 15. Thelaundry washing machine of claim 13, wherein the controller isconfigured to initiate the color decision algorithm by communicatingdata from the plurality of color composition data captures to a remotedevice that executes at least a portion of the color decision algorithm,and wherein the controller is further configured to receive result dataassociated with the color decision algorithm from the remote device. 16.The laundry washing machine of claim 13, wherein the color decisionalgorithm is configured to assign each of the plurality of pixels in thecaptured color composition data to one of the plurality of colorcategories by comparing color data for each pixel against a plurality ofthresholds associated with the plurality of color categories.
 17. Thelaundry washing machine of claim 13, wherein the color decisionalgorithm is configured to determine a number of pixels in the capturedcolor composition data that are assigned to each of the plurality ofcolor categories, and to characterize the load of articles based uponthe determined numbers of pixels.
 18. The laundry washing machine ofclaim 17, wherein the color decision algorithm is configured tocharacterize the load of articles based upon the determined numbers ofpixels by comparing the determined numbers of pixels against thresholdsassociated with one or more of the plurality of color categories. 19.The laundry washing machine of claim 18, wherein the plurality of colorcategories to which the pixels are assigned includes a whites colorcategory, a lights color category, and a darks color category, andwherein the color decision algorithm is configured to characterize theload of articles based upon the determined numbers of pixels by:characterizing the load of articles as a whites load in response to amajority of the determined numbers of pixels being assigned to thewhites color category and the determined number of pixels assigned tothe whites color category meeting a whites threshold; characterizing theload of articles as a lights load in response to a majority of thedetermined numbers of pixels being assigned to the lights color categoryand the determined number of pixels assigned to the lights colorcategory meeting a lights threshold; and characterizing the load ofarticles as a darks load in response to a majority of the determinednumbers of pixels being assigned to the darks color category and thedetermined number of pixels assigned to the darks color category meetinga darks threshold.
 20. The laundry washing machine of claim 19, whereinthe plurality of color categories further includes a reds colorcategory, and wherein the color decision algorithm is further configuredto characterize the load of articles as a reds load in response to thedetermined number of pixels assigned to the reds color category meetinga reds threshold.
 21. A laundry washing machine, comprising: a wash tubdisposed within a housing; a color detection sensor positioned tocapture color composition data of a load of articles as the load ofarticles is added to the wash tub; a weight sensor operatively coupledto the wash tub to sense a weight of the load of articles as the load ofarticles is added to the wash tub; and a controller coupled to the colordetection sensor and the weight sensor and configured to initiate aplurality of color composition data captures with the color detectionsensor responsive to detected weight changes sensed by the weight sensoras the load of articles is added to the wash tub, the controllerconfigured to initiate each color composition data capture in responseat least in part to the weight sensor detecting a stable weight in thewash tub for at least a predetermined duration; wherein the controlleris further configured to set one or more operational settings for a washcycle based upon the plurality of color composition data captures;wherein the controller is configured to initiate the plurality of colorcomposition data captures in response to detecting an open door, and todetermine that all articles in the load have been added to the wash tubin response to detecting a closed door; wherein the controller isconfigured to initiate an additional capture of color composition dataafter detecting the closed door if a weight sensed by the weight sensoris greater than a predetermined constant.
 22. A laundry washing machine,comprising: a wash tub disposed within a housing; a color detectionsensor positioned to capture color composition data of a load ofarticles as the load of articles is added to the wash tub; a weightsensor operatively coupled to the wash tub to sense a weight of the loadof articles as the load of articles is added to the wash tub; and acontroller coupled to the color detection sensor and the weight sensorand configured to initiate a plurality of color composition datacaptures with the color detection sensor responsive to detected weightchanges sensed by the weight sensor as the load of articles is added tothe wash tub, the controller configured to initiate each colorcomposition data capture in response at least in part to the weightsensor detecting a stable weight in the wash tub for at least apredetermined duration; wherein the controller is further configured toset one or more operational settings for a wash cycle based upon theplurality of color composition data captures; wherein the controller isconfigured to initiate the plurality of color composition data capturesin response to detecting an open door, and to determine that allarticles in the load have been added to the wash tub in response todetecting a closed door; and wherein the controller is configured tostart a sleep timer in response to detecting the open door, to reset thesleep timer in connection with each color composition data capture, toput the laundry washing machine in a sleep state in response toexpiration of the sleep timer, and to awaken the laundry washing machineand initiate a color composition data capture in response to detectionof a weight change by the weight sensor while the laundry washingmachine is in the sleep state.